Magnetic resonance imaging device and method

ABSTRACT

A magnetic resonance imaging method for fully automatically forming a water/fat separated image by calculation after acquiring data on images of different echo times, wherein the unwrapping of a phase map showing the distribution of the phase rotation due to the inhomogeneous static magnetic field is repeated so as to determine the distribution of the inhomogeneous static magnetic field by using an index used for judging whether or not the unwrapping is properly being performed, and wherein during the formation of a water/fat separated image with correction of the static magnetic field, the unwrapping is automatically and properly performed in correcting the static magnetic field, and the water/fat images are automatically discriminated.

FIELD OF THE INVENTION

[0001] The present invention relates to a magnetic resonance imagingdevice (hereinafter will be referred to as MRI device) and method, and,more particularly, relates to an MRI device and method which achieves anautomatic separation between water imaging and fat imaging.

BACKGROUND ART

[0002] An imaging object of an MRI device which becomes widespread inclinical application is protons which are a major constituent materialof an inspection subject. Through imaging such as a spatial distributionof proton density and a spatial distribution of relaxation attenuationof excitation state, configurations or functions of such as a humanhead, abdomen and extremity are imaged in two dimension or threedimension.

[0003] Protons exist such as in water and fat in human tissue, however,their chemical shifts differ depending on their combinationconfigurations. By making use of such chemical shift difference manyapproaches of drawing separately an image of protons in water and animage of protons in fat have been proposed. For example, as an examplemethod of acquiring a fat suppressed image, a method, in which aplurality of images having different echo times (TE) are obtained andthen water and fat separated images are acquired through computationthereof, is enumerated. A typical method therefor is disclosed in“Simple Proton Spectroscopic Imaging” by W. Thomas Dixon et al.,(RADIOLOGY Vol. 153, pp 189-194 (1984)), which hereinbelow will bereferred to as Dixon method. Methods of acquiring water and fatseparated images through computation other than Dixon method are knownand disclosed, for example, in the following papers “Water-Fat Imagingwith Three-Point Direct Phase Encoding” by Qing-San Xiang and Li An,(Proc., SMR 3rd Meeting. p 658 (1995)), “Quadrature 2-point Water-FatImaging”, by Li An and Qing-San Xiang, (Proc., ISMRM 4th ScientificMeeting, p 1541 (1996)), and “Water-Fat Imaging withThree-Orthogonal-Phase Acquisitions” by Li An and Qing-San Xiang,(Proc., ISMRM Scientific Meeting, p 1866 (1998)).

[0004] These methods are common in the following aspect, in which imagedata of a plurality of images are acquired from a plurality of echosignals having different times (echo time TE) from nuclear spinexcitation to generation of signals and the imaging is performed byseparating water signals and fat signals through computation of theacquired image data.

[0005] These methods in which the water and fat separated images areacquired by performing computation with regard to the plural imagesprepared from the plural signals having such different echo times TEinclude the following problems. One problem is that an unintended phaseoffset is caused in the signal due to such as inhomogeneous staticmagnetic field and local magnetic field turbulence, and another problemis that an image obtained by the computation is difficult todiscriminate between a water image and a fat image.

[0006] The first problem is caused by such as distortion of a magnetwhich generates the static magnetic field and the performance limitationof the magnet itself as well as may be caused by magnetic susceptibilitydifference in respective portions of an inspection subject, when thesame being placed in an MRI device. A static magnetic fieldinhomogeneity in Field of View (FOV) of an MRI image causes to varyfrequencies of MR signals and causes an image quality deterioration suchas a position displacement and flow in the acquired image. Further,because of phase variation in images due to the static magnetic fieldinhomogeneity it is difficult of obtain a correct result, whenperforming a complex computation between images.

[0007] In connection with the above referred to water and fat imageseparation, as a method of resolving the problem with regard to thephase offset due to the static magnetic field inhomogeneity, such as2-point Dixon method and 3-point Dixon method in which a function ofcorrecting the influence due to the static magnetic field inhomogeneityis added to the Dixon method are proposed, for example, in “Two-PointDixon Technique for Water-Fat Signal Decomposition with BO InhomogeneityCorrection” by Bernard D. Cooms et al., (Magnetic Resonance in Medicine,Vol. 38, pp 884-889 (1997)).

[0008] The above referred to method will be explained in connection with2-point Dixon method. In the 2-point Dixon method, signals are acquiredat timings when phases of proton in water and proton in fat are inin-phase and in anti-phase due to their chemical shift difference asillustrated in FIG. 1. In FIG. 1, 102 and 103 are respectively gradientmagnetic field pulses for generating echo signals S1 and S2, and in thesignal S1 a signal component 105 from water protons and a signalcomponent 104 from fat protons are contained and in the signal S2 asignal component 107 from water protons and a signal component 106 fromfat protons are contained.

[0009] Herein, the timing of acquiring the first echo signal (firstecho) S1 is determined at a timing when 2nτ (wherein n is a positiveinteger, which is also true throughout the present specification) haselapsed after a high frequency magnetic field pulse 101 is generated,wherein when assuming difference of resonance frequencies of waterprotons and fat protons is Δf, 2τ=1/Δf, and the timing of acquiring thesecond echo signal (second echo) S2 is when τ has elapsed after thefirst echo.

[0010] When no phase offset due to the above referred to static magneticfield inhomogeneity is induced until the acquisition of the first andsecond echoes after generation of the high frequency magnetic fieldpulse 101, a water image and a fat image are obtained throughcomputation between an image (first echo image) obtained from the firstecho signal and an image (second echo image) obtained from the secondecho signal according to the following equations:

S 1(x, y)=W(x, y)+F(x, y)   (1)

S 2(x, y)=W(x, y)−F(x, y)   (2)

S 1(x, y)+S 2(x, y)=2W(x, y)   (3)

S 1(x, y)−S 2(x, y)=2F(x, y)   (4)

[0011] wherein, S1(x, y) represents the first echo, S2(x, y) representsthe second echo, and W(x, y) and F(x, y) respectively representmagnitudes of signal due to water protons and of signal due to fatprotons in the respective echo signals.

[0012] Now, when a phase offset exists in the signals, the first echosignal and the second echo signal are expressed as follows;

S 1(x, y)=(W(x, y)+F(x, y))exp(i(α(X, y)))   (5)

S 2(x, y)=(W(x, y)−F(x, y))exp(i(α(X, y)+φ(x, y)))   (6)

[0013] wherein, α(x, y) is a phase rotation component due to such asinhomogeneity of RF magnetic field pulse in the vector direction, butindependent from time and, in the case of the gradient echo (GrE)sequence as illustrated in FIG. 1, contains a phase rotation componentcaused during the time TE (wherein 2nπ) due to the static magnetic fieldinhomogeneity, and φ(x, y) is a phase rotation component due to thestatic magnetic field inhomogeneity.

[0014] As will be seen from the above, where there exists a staticmagnetic field inhomogeneity, a difference in phases of the first echoand the second echo is caused, thereby, the water signal and the fatsignal can not be separated through the simple addition and subtractionas with the equations (3) and (4). Accordingly, in the Dixon method inwhich the function of correcting the influence due to the staticmagnetic field inhomogeneity is added, at first a phase offset φ(x, y)due to the static magnetic field inhomogeneity is determined throughcomputation between two echoes, then, after correcting the phase offset,the water and fat image separation is performed through addition andsubtraction.

[0015] The 2-point Dixon method with static magnetic field correctionmakes use of the fact that the phase difference between a water signaland a fat signal in S2 signal is π in order to determine the phaseoffset. Namely, when doubles π makes 2π, therefore, in view of principalvalue rotation the doubled value becomes equivalents to that with norotation. Therefore, through subtracting the phase of S1(x, y) from thatof S2(x, y) and doubling the resultant difference, a static magneticfield inhomogeneity map can be determined.

[0016] Further, in 3-point Dixon method three signals S1, S2 and S3 eachhaving different echo time is obtained as shown in FIG. 2 and a phaserotation amount 2φ(x, y) is determined depending on a ratio between thefirst echo S1 and the third echo S3 in which the water signals and thefat signals are in in-phase. In FIG. 2, 202, 203 and 204 arerespectively gradient magnetic field pulses for causing the echo signalsS1, S2 and S3, and 206, 209 and 212 are water signals and 205, 208 and211 are fat signals.

[0017] When determining the phase rotation amount due to the staticmagnetic field inhomogeneity in such Dixon methods with static magneticfield correction, a processing for eliminating the principal valuerotation, namely a processing called as unwrapping or rewinding isrequired. Methods of unwrap processing are disclosed in the abovereferred to papers as well as the following papers; “Direct Calculationof Wrap-Free Phase Image” by M. Patel and X. Hu, (Proceedings of AnnualMeetings of the Society of Magnetic Resonance in Medicine (=SMRM). No.721, (1993)) and “Phase unwrapping in the Three Point Dixon Method forFat Suppression MR Imaging” by Jerzy Szmowski et al., (Radiology, Vol.192, pp 555-561 (1994)).

[0018] However, such unwrapping (rewinding) shows a problem of beingsusceptible to influence of noises. In particular, with regard to the2-point Dixon method since the second echo signal has to be obtained atthe timing when the phases of the water protons and the fat protons arein anti-phase, the difference between the water signal and the fatsignal forms the second echo signal, therefore, of which intensity issmall which is significantly affected by noises. In order to eliminatesuch influence of noises, some measures such as omitting the unwrapprocessing by masking regions which are susceptible to noises isnecessitated, however, since such regions which are susceptible tonoises vary depending on respective images, it was difficult to set andselect proper noise removal masks for every unwrap processing.

[0019] With regard to the second problem that it is difficult todiscriminate whether an image obtained by the computation is a waterimage or a fat image, such discrimination is theoretically possible, ifthe unwrap starting point is optimized in order to eliminate the phaseoffset of 2nπ caused in association with the unwrap processing. However,since there are no methods of optimizing automatically the unwrapstarting point, measures of such as visually designating the startingpoint and of deciding which is the water image by visually observing theresultant image are taken and any automatic separation between a waterimage and a fat image is not realized until now.

[0020] Accordingly, an object of the present invention is to provide anMRI device provided with a function of acquiring a water image and a fatimage through computation between images obtained from plural echosignals having different echo times which permits static magnetic fieldcorrection including a proper unwrap processing and further permits anautomatic discrimination between the water image and the fat image.Thereby, another object of the present invention is to provide an MRIdevice which permits an automatic acquisition of separated water and fatimages.

[0021] Further, still another object of the present invention is toprovide an MRI method with imaging method including a static magneticfield correction processing in an MRI device which permits automaticoptimization of unwrap processing.

DISCLOSURE OF THE INVENTION

[0022] In order to resolve the above tasks, an MRI device according to afirst aspect of the present invention which is provided with a magneticfield generation means which respectively generates a high frequencymagnetic field and a gradient magnetic field in a space where a staticmagnetic field is formed, a signal processing means which detects anuclear magnetic resonance signal generated from an inspection subjectplaced in the space and reconstructs an image therefrom and a displaymeans which displays the reconstructed image, characterized in that thesignal processing means performs, by making use of at least more thanone nuclear magnetic resonance signals having different times (TE) fromirradiation of the high frequency signal and generation of the nuclearmagnetic resonance signals, a computation for determining a phase offsetdistribution-between the signals, an unwrap processing for correcting aprincipal value rotation caused in the computation and at the same timeperforms a judgement whether the unwrap processing is proper by makinguse of a parameter representing the unwrap processing state.

[0023] In the unwrap processing according to the present invention,plural noise removal masks are employed and are applied in a step bystep manner. Further, in parallel with advancement of the unwrapprocessing, a parameter indicating whether or not any inconsistency inthe unwrap processing occurs is at the same time prepared, and theproperness of the unwrap processing is judged based on the parameter.When it is judged that the unwrap processing is improper, another unwrapprocessing is performed by adding another type of noise removal-mask orby varying parameter (such as a threshold value used when preparing amask) of the mask. When it is judged that the unwrap processing isproper based on the parameter indicating the unwrap processing state,the unwrap processing result is determined as the phase offsetdistribution. The phase offset distribution determined herein istypically caused by such as a static magnetic field inhomogeneity butsometimes includes those caused by such as a local phase turbulence.

[0024] The noise removal masks used in the unwrap processing accordingto the present invention include either one which is prepared from anabsolute value image of the first echo signal, one which is preparedfrom an absolute value image of the second echo signal or one which isprepared from both the above, or a combination thereof.

[0025] Further, as a noise removal mask used in the unwrap processingaccording to the present invention, a mask (which will be hereinafterreferred to as a loop mask) can be used which is obtained when scanningthe entire images in such a manner that while assuming a closed loop ona map representing the phase rotation amount distribution due to thestatic magnetic field inhomogeneity, and when a phase differenceaccumulation value taken around the closed loop is 2nπ (wherein n is apositive integer), the points on the closed loop are masked. Such loopmask can also be used in parallel with the above referred to masksprepared by the absolute value image of the first echo and/or theabsolute value image of the second echo.

[0026] The above first aspect of the present invention can be applied toan MRI device provided with a function which, by making use of at leastmore than one nuclear magnetic resonance signals having different times(TE) from irradiation of the high frequency magnetic field to generationof the nuclear magnetic resonance signals, reconstructs an image withregard to two types of unclear spins having different chemical shiftsthrough computation between the signals.

[0027] Namely, such MRI device is characterized, in that by making useof at least more than one types of nuclear magnetic resonance signalshaving different times (TE) from irradiation of the high frequencymagnetic field to generation of the nuclear magnetic resonance signals,the signal processing means performs the computation for determining thephase offset distribution between the signals, the unwrap processing forcorrecting the principal value rotation caused in the computation and atthe same time performs the processing of judging properness of theunwrap processing by making use of the parameter representing the unwrapprocessed state, further corrects the nuclear magnetic resonance signalsbased on the phase offset distribution of properly unwrap processed,thereafter, the image with regard to the two types of nuclear spinshaving different chemical shifts is reconstructed through thecomputation between the signals.

[0028] Further, an MRI device according to a second aspect of thepresent invention which is provided with a magnetic field generationmeans which respectively generates a high frequency magnetic field and agradient magnetic field in a space where a static magnetic field isformed, a signal processing means which detects a nuclear magneticresonance signal generated from an inspection subject placed in thespace and reconstructs an image therefrom and a display means whichdisplays the reconstructed image, characterized in that the signalprocessing means, by making use of at least more than one nuclearmagnetic resonance signals having different times (TE) from irradiationof the high frequency signal and generation of the nuclear magneticresonance signals, reconstructs more than one original images, furtherreconstructs two types of display images with regard to two types ofnuclear spins having different chemical shifts through computationbetween these original images and performs an automatic discriminationon the correspondence between the obtained two types of the displayimages and the two types of the nuclear spins from a ratio of pixelvalues of the more than one original images and/or pixel values of thetwo types of the display images.

[0029] When reconstructing the two types of images (display images)through the computation (addition and subtraction) between the images(original images) obtained from the signals having different echo times,by making use of two parameters, namely (1) a ratio of pixel values ofmore than one original images, and (2) pixel values of the two types ofthe display images, the types of the display images can be correctlydiscriminated. More specifically, these two parameters are determined(1) through comparison of the ratios of signal values of two originalimages in an intense signal region which are respectively extracted froman addition image obtained by adding the original images and asubtraction image obtained by subtracting the original images and (2)through comparison of the pixel values in an intense signal region whichare respectively extracted from the addition image and the subtractionimage.

[0030] The two types of display images are typically the water image andthe fat image, however, the same can be likely applied to materials suchas water and silicon and water and NAA to which the chemical shiftdifference can be made use of.

[0031] Further, an MRI device according to a further aspect of thepresent invention which is provided with a magnetic field generationmeans which respectively generates a high frequency magnetic field and agradient magnetic field in a space where a static magnetic field isformed, a signal processing means which detects a nuclear magneticresonance signal generated from an inspection subject placed in thespace and reconstructs an image therefrom and a display means whichdisplays the reconstructed image, characterized in that the signalprocessing means performs, by making use of at least more than onenuclear magnetic resonance signals having different times (TE) fromirradiation of the high frequency signal and generation of the nuclearmagnetic resonance signals, a computation for determining a phase offsetdistribution between the signals, an unwrap processing for correcting aprincipal value rotation caused in the computation and at the same timeperforms a judgement whether the unwrap processing is proper by makinguse of a parameter representing the unwrap processing state, andfurther, by making use of the nuclear magnetic resonance signalscorrected based on the phase offset distribution judged as properlyunwrap processed, reconstructs more than one original images, furtherreconstructs two types of display images with regard to two types ofnuclear spins having different chemical shifts through computationbetween these original images and performs an automatic discriminationon the correspondence between the obtained two types of the displayimages and the two types of the nuclear spins from a ratio of pixelvalues of the more than one original images and/or pixel values of thetwo types of the display images.

[0032] The above MRI device can realized an automatic operation by meansof the incorporation of an automatic optimization processing of theunwrap processing and an automatic discrimination processing of thedisplay images, when reconstructing the two types of images (displayimages) through the computation between the images (original images)obtained from the signals having different echo times.

[0033] The MRI device according to the present invention can be simplyapplied to the 2-point Dixon method with static magnetic fieldcorrection, thereby, separated water and fat images can be obtained in afull automatic manner. Further, since the measurement time of 2-pointDixon method is short in comparison with that by 3-point Dixon method,thereby, the repetition time (TR) of the sequence can be shortened.Thus, when assuming that the repetition times (TR) are the same, thenumber of images obtained in multi-slices can be increased. Stillfurther, since direct correction of the phases between two data isperformed, influences such as due to eddy current can be eliminated in100%, thereby, the present invention is suitable for an open type MRIdevice in which such as static magnetic field inhomogeneity and magneticfield turbulence due to gradient magnetic field coils are significant.

BRIEF DESCRIPTION OF THE DRAWINGS

[0034]FIG. 1 is a time chart of data acquisition in a 2-point Dixonmethod;

[0035]FIG. 2 is a time chart of data acquisition in a 3-point Dixonmethod;

[0036]FIG. 3 is a schematic diagram of an MRI device to which thepresent invention is applied;

[0037]FIG. 4 is a time chart of data acquisition in a 2-point Dixonmethod which is employed in the present invention;

[0038]FIG. 5 is a diagram showing an example of a processing flow in aDixon method with static magnetic field correction according to thepresent invention;

[0039]FIG. 6 is a diagram showing an example of phase 2φ map preparationflow according to the present invention;

[0040] FIGS. 7(a) and (b) are diagrams for explaining a loop maskaccording to the present invention;

[0041] FIGS. 8(a) through (d) are diagrams showing in image forms anunwrap processing state according to the present invention;

[0042] FIGS. 9(a) through (f) are diagrams for explaining a preparationmethod of an unwrap processing state map according to the presentinvention;

[0043]FIG. 10 is diagram showing an embodiment of an automatic unwrapprocessing flow according to the present invention;

[0044] FIGS. 11(a) through (c) are diagrams showing in image forms aphase aligning state after unwrap processing according to the presentinvention;

[0045]FIG. 12 is a diagram showing another embodiment of an automaticunwrap processing flow according to the present invention;

[0046] FIGS. 13(a) and (b) are diagrams showing in image forms ofmeasurement of a growing unwrap processing in the processing flow asshown in FIG. 12;

[0047]FIG. 14 is a diagram for explaining in an image form of one stepin an unwrap properness judgement processing according to the presentinvention;

[0048]FIG. 15 is a diagram showing still another embodiment of anautomatic unwrap processing flow according to the present invention;

[0049]FIG. 16 is a diagram showing a flow in which a matrix reducingstep is introduced in to a processing flow of the Dixon method withstatic magnetic field correction as shown in FIG. 5;

[0050]FIG. 17 is a diagram for explaining the matrix reducing method asshown in FIG. 16;

[0051] FIGS. 18(a) and (b) are time charts for data acquisition with a3-point Dixon method which is employed in the present invention;

[0052] FIGS. 19(a) through (e) are diagrams for explaining in imageforms an example of an automatic discrimination algorism of water andfat images according to the present invention; and

[0053] FIGS. 20(a) through (f) are diagrams for explaining in imageforms another example of an automatic discrimination algorism of waterand fat images according to the present invention.

BEST EMBODIMENTS FOR CARRYING OUT THE PRESENT INVENTION

[0054] Hereinbelow, embodiments of the present invention will beexplained with reference to the drawings. Further, among the drawingswhich will be used for the explanation below, FIGS. 8, 11, 13, 14, 19and 20 are photos which are prepared in image forms for explainingprocessings performed in the present embodiments.

[0055]FIG. 3 shows a constitutional diagram of an MRI device to whichthe present invention is applied. The MRI device is provided with amagnet 302 which generates a static magnetic field in a spacesurrounding an inspection subject 301, a gradient magnetic field coils303 which induce magnetic field gradients in the space in threedirections of X, Y and Z, an RF coil 304 which generates a highfrequency magnetic field for causing nuclear spins of atoms constitutingthe tissue of the inspection subject 301 a nuclear magnetic resonanceand an RF probe 305 which detects NMR signals generated from theinspection subject 301 by the nuclear magnetic resonance. The MRI deviceis further provided with a gradient magnetic field power source 309serving as a power source for the gradient magnetic field coils 303, asignal transmission unit 310 which drives the RF coil 304, a signaldetection unit 306 which detects the NMR signals from the RF probe 305,a signal processing unit 307 which processes the signals, a control unit311 which controls the gradient magnetic field power source 309, thesignal detection unit 306 and the signal processing unit 307, and adisplay unit 308 which displays the processed result by the signalprocessing unit 307. A bed 312 is for laying the inspection subject 301thereon.

[0056] In such constitution, after carrying in the inspection subject301 into a space of homogeneous static magnetic field produced by themagnet 302, the RF coil 304 generates in response to the signals fromthe RF signal transmission unit 310 high frequency magnetic fieldshaving frequencies which cause nuclear spins of atoms (hereinbelow willbe referred to simply as spin) constituting the tissue of the inspectionsubject 301 nuclear magnetic resonances. The objective spins in thepresent embodiment are protons which are the major constituent materialof the inspection subject 301.

[0057] The gradient magnetic field coils 303 are constituted by gradientmagnetic field coils in three directions of X, Y and Z and generaterespective magnetic fields in response to signals from the gradientmagnetic field power source 309. With the gradient magnetic field aregion of the inspection subject 301 where the nuclear magneticresonances are caused is selected as well as positional information isprovided for the NMR signals.

[0058] The signals from the RF probe 305 are detected by the signalprocessing unit 307 and further converted into image signals throughcomputation. The images are displayed on the display unit 308.

[0059] The control time chart, which controls the generation of theabove referred to high frequency magnetic field and the gradientmagnetic fields and the measurement of the NMR signals, is called aspulse sequence, and which is stored in the control unit 311 as a presetprogram. In the embodiment of the present invention which will beexplained hereinbelow, a pulse sequence so called 2-point Dixon methodis executed in which at least two NMR signals having different echotimes are measured in one sequence to be repeated, and an image whichprimarily draws water protons (hereinbelow will be referred to as waterimage) and an image which primarily draws fat protons (hereinbelow willbe referred to as fat image) are obtained. Further, when reconstructingthe images by having the NMR signals, a computation is added whichcorrects the static magnetic field inhomogeneity by making use of thetwo NMR signals having different echo times.

[0060] Hereinbelow, the signal measurement and the magnetic fieldcorrection computation according to the present embodiment will beexplained in detail.

[0061]FIG. 4 shows a pulse sequence according to a 2-point Dixon methodemployed in the present embodiment. In this pulse sequence, at first anRF pulse 401 is irradiated to excite spins of an inspection subject. Inthis instance, a slice selection gradient magnetic field Gs forselecting a specific slice of the inspection subject is applied at thesame time with the RF pulse 401. Subsequently, a phase encode gradientmagnetic field Gp for phase-encoding the NMR signals is applied, andthen another RF pulse 402 for inverting the spins is irradiated togetherwith a slice selection gradient magnetic field Gs. Thereafter, aread-out gradient magnetic field Gr 403 is applied and after time TEfrom irradiation of the first RF pulse 401 an echo signal (first echo)is measured, and further another read-out gradient magnetic field Gr 405of which polarity is inverted from the former is applied and after timeT from the measurement of the first echo 404 an echo signal (secondecho) 406 is measured.

[0062] The above sequence is repeated predetermined times, for examplesuch as 128 times and 256 times, while varying the intensity of thephase encode gradient magnetic field Gp to obtain a necessary number ofecho signals for an image reconstruction. Namely, with the sequences oneimage (first echo image) is formed by the first echoes of which numbercorresponds to the repetition number and another image (second echoimage) is formed by the second echoes of which number also correspondsto the repetition number. These formed images are used as originalimages in a computation for determining a water image and a fat imagewhich will be explained later.

[0063] Further, in FIG. 4 a spin echo type pulse sequence in which afterirradiation of the RF pulse 401 the inverting RF pulse is used isexemplified, however, the gradient echo type pulse sequence as shown inFIG. 1 can also be used. Both in the spin echo type and gradient echotype pulse sequences, two signals having different echo times within onerepetition time as shown in FIG. 4 can be measured as well as twosignals having different echo times can be measured with twicemeasurements as shown in FIG. 1.

[0064] In such pulse sequence, at the timing when the first echo 404 ismeasured, the phases of the water proton spins (hereinafter will bereferred to as water spin) and of the fat proton spins (hereinafter willbe referred to as fat spin) are in in-phase, however, after lapsing timeτ a phase offset is caused due to difference in resonance frequencies ofthe water spin and the fat spin, and after time τ the phases deviate by180° each other.

[0065] Namely, since the water proton and fat proton perform precessionwith different frequencies fow and fof, the relative orientation oftheir magnetization vectors (spins) of the water protons and the fatprotons is caused to offset in accordance with lapse of time. Whenassuming that the difference between the resonance frequencies of waterprotons and the fat protons is Δf, then 2τ=1/Δf, and when the waterspins and the fat spins orient in the same direction at a certainmoment, the same orient in the reverse direction (180°), in the samedirection (360°) . . . after every τ.

[0066] In FIG. 4 pulse sequence, since the RF pulse 402 for invertingthe spins is used, after time TE/2 from the irradiation of the RF pulse402, the phases of the water spins and the fat spins are aligned andafter elapsing τ the phases thereof are inverted each other.

[0067] As has been explained in Background Art, when assuming that imagesignals which are obtained by processing respectively these two NMRsignals as S1(x, y) and S2(x, y) and the signal magnitudes due to waterand fat among these signals are respectively as W(x, y) and F(x, y), thefollowing equations (equations (1) and (2)) stand;

S 1(x, y)=W(x, y)+F(x, y)   (1)

S 2(x, y)=W(x, y)−F(x, y)   (2)

[0068] Accordingly, when adding S1(x, y) and S2(x, y), a water image asthe addition image is obtained (equation (3)) and when subtracting thesame, a fat image as the subtraction image is obtained (equation (4));

S 1(x, y)+S 2(x, y)=2W(x, y)   (3)

S 1(x, y)−S 2(x, y)=2F(x, y)   (4)

[0069] The precondition when the above equations (3) and (4) stands isthat at the measurement timings of the first echo 404 and of the secondecho 406, the phase relationship of the water spin and the fat spin isinverted and the phase of the water signal is unchanged, however, inreality due to such as static magnetic field inhomogeneity, the spinrotation is affected, which is expressed by the following equations;

S 1(x, y)=(W(x, y)+F(x, y))exp(i(α(x, y)))   (5)

S 2(x, y)=(W(x, y)−F(x, y))exp(i(α(X, y)+φ(X, y)))   (6)

[0070] wherein, φ(x, y) is a phase rotation component due to the staticmagnetic field inhomogeneity and α(x, y) is a phase rotation componentdue to inhomogeneity of RF pulses in the vector direction.

[0071] Accordingly, when obtaining the water image and the fat image byaddition and subtraction of the first and second echoes 404 and 406, itis necessary to correct the phase rotation of the signals. For thispurpose, the phase rotation amount φ is determined by making use ofthese two signals and with the determined phase rotation amount φ theprocessing for the phase correction is performed of which dataprocessing algorism is shown in FIG. 5.

[0072] In this data processing, other than step 507 in which separatedwater and fat images are obtained through addition and subtraction of afirst echo 506 and a second echo 501, a module 509, a portion surroundedby a dotted line, in which a phase 2φ map representing distribution ofstatic magnetic field inhomogeneity is prepared by making use of theseechoes 506 and 501 and step 502 which corrects the phase of the secondecho 501 are included. The phase 2φ map is one which determines thephase rotation caused due to the static magnetic field inhomogeneity asa function of positions. After correcting the phase of the second echobased on the thus prepared phase 2φ map, the water and fat images 508are obtained through the addition and subtraction processing 507.

[0073] The phase 2φ map preparation step 509 includes a phase 2φ mappreparation before unwrap step 503, an unwrap processing step 504 and anunwrap properness judgement step 505. Hereinbelow, the function of thephase 2φ map preparation module will be explained in further detail.

[0074] At first, in the phase 2φ map preparation step 503 the phase ofS1(x, y) is subtracted from that of S2(x, y) and the remained phase isdoubled to determine a static magnetic field inhomogeneity map, which isexpressed by the following equations;

S 1*(x, Y)/|S 1(x, y)|=exp {−iα(X, y)}  (7)

S 2(x, y)×{S 1*(x, y)/|S 1(x, y)|}=(W(x, y)−F(x, y))exp {iα(X, y)}  (8)

{S 2(x, y)×(S 1*(x, y)/|S 1(x, y)|)}² /S 2(x, y)|={(W(x, y)−F(x, y)}²/|W(x, y)−F(x, y)|esp {i2φ(X, y)}=|W(x, y)−F(x, y)| exp(i2φ(x, y))   (9)

[0075] when taken an argument of equation (9), 2φ(x, y) can bedetermined. Further, arg ( ) implies to determine the phase.

[0076] Subsequently, an unwrap processing is performed on the thusdetermined phase 2φ map. As will be well known, since phases “φ1” and“φ1+2π” are recognized as the same phase, when the phase distributionregion exceeds over 2π, the phases “φ1” and “φ1+2π” can not bediscriminated, thereby, discontinuous portions with regard to phasevariation are caused (which is called as principal value rotation). Thephase unwrap processing is a processing for eliminate such principalvalue rotation, more specifically, is a processing in which phases of apredetermined reference point and of an adjacent point (a point to beunwrapped) are respectively determined, and if the difference Δφ thereofis outside a predetermined range (usually −π≦Δφ≦π), it is determinedthat the principal value rotation has occurred, and 2π is added orsubtracted to and from the phase value of the adjacent point.Alternatively, such processing is performed, in that after determiningthe phase difference between the reference point and the point to beunwrapped through complex computation and expressing the same as a phasevalue, the phase of the present point to be unwrapped is determined byadding the phase value to the phase of the reference point. In thisinstance, the point to be unwrapped can be directly determined withoutadding ±2π to the point to be unwrapped. These phase unwrap processingsare usually performed for all of the pixels while successively changingthe reference point.

[0077] In the present invention, such unwrap processing is not performedwith regard to all of the coordinate points on the obtained phase map,but regions in which influences of noises are intense are excludedbeforehand by making use of a proper noise removal mask and the unwrapprocessing is performed only over the remaining regions. This is becausethe phase rotation amount due to the static magnetic field inhomogeneityis determined by making use of the second echo which is obtained at thetiming when phases of the water spin and the fat spin are in anti-phase,therefore, the amount of noise increases and artifact is likely tooccurs, consideration of which is particularly important when the2-point Dixon method is employed in the present invention.

[0078] In the present embodiment, as the noise removal mask thefollowing masks are used in combination, (a) a mask (first echothreshold mask) which is prepared in such a manner that an absolutevalue of the first echo is determined and when the absolute value ismore than a preset threshold value, the mask shows 1 and when less thanthe preset threshold value, the mask, shows 0, (b) a mask (second echothreshold mask) which is prepared in such a manner that an absolutevalue of the second echo is determined and when the absolute value ismore than a preset threshold value, the mask shows 1 and when less thanthe preset threshold value, the mask shows 0, and (c) a loop mask whichis prepared in such a manner that a closed loop is assumed on the phasedistribution map and when the accumulated phase difference value aroundthe closed loop is 2nπ, the points on the closed loop are determined 0(in other words pop-up points are patched).

[0079] In the unwrap properness judgement step 505, properness ofunwrapping result after effecting the above referred to masking isjudged, and if it is judged the unwrap processing is not properlyperformed, another unwrap processing is again performed which changesthe condition of masking, and the same processing (504 and 505) isrepeated until a proper unwrap processing is effected.

[0080]FIG. 6 is a diagram showing a processing flow in the phase 2φ mappreparation module, and in the illustrated embodiment, at first prior tothe unwrap processing the first echo threshold mask is prepared from thefirst echo (step 601), the prepared mask is applied to the phase 2φ mapprepared at step 602 and only a portion where the inspection subjectexists is extracted among the phase 2φ map. Subsequently, in order toadvance the unwrap processing smoothly, the phase 2φ map prior to theunwrapping is smoothed by making use of a low pass filter (LPF) 603.

[0081] The subsequent unwrap processing module includes a loop maskpreparation module 604 serving as the noise removal mask for the phase2φ map, a region growing unwrap processing algorism 605 and a fittingmodule 606 for non-unwrap region.

[0082] As shown in FIGS. 7(a) and 7(b), the loop mask preparation module604 prepares a loop having sides of a predetermined length, for example,a loop of 2×2, while using a certain point (in the drawing a pixelindicated in gray color) as a reference and phase sum (an accumulationsum of the phase differences with adjacent pixels) of the points on theloop. If no phase disturbance due to noises exists, the phase sum isnaturally 0, therefore, if the determined phase sum is 0, the referencepoint is shifted without masking and the same processing is repeated. Onthe other hand, if the phase sum is not 0, it is understood that adisturbance in phase is caused, therefore, points on the loop aremasked. Then, length of one side of the loop is increased, for example,3×3 loop is formed and the phase sum of the points on the new loop isdetermined, if the phase sum is not 0, the length of one side is furtherincreased. In this manner, the processing is repeated while expandingthe loop until the phase sum of the points on the loop becomes 0.Further, when the length of one side of the loop reaches a predeterminedmaximum value, such processing is terminated and the reference point isshifted.

[0083] Generally, when the maximum value of one side of a loop mask istoo small, regions which affect noises can not be properly removed, onthe other hand, when the maximum value is too large, the unwrapprocessing can not be performed properly. Accordingly, in the presentembodiment the maximum value of one side is set as small as possible atthe first time and when it is judged at the unwrap properness judgementstep 505 that the unwrap processing is not performed properly, themaximum value is gradually increased. With this measure, a maskingbeyond the necessity is prevented.

[0084] As has been explained previously, the region growing unwrapprocessing algorism 605 is a processing in which while selecting apredetermined point as a starting point, the phase differences betweenadjacent points including the starting point is successivelyinvestigated and when the phase difference is outside the predeterminedrange, 2π is added or subtracted to the phase of the concerned adjacentpoint or alternatively, after determining the phase difference betweenthe reference point and the point to be unwrapped through complexcomputation and expressing the same as a phase value, the phase of theconcerned adjacent point is determined by adding the phase value to thephase of the reference point. Candidates of the starting point whichserves as the first reference point are picked out from points nearcenter portion of FOV and one of the candidates on which the unwrapprocessing is most frequently performed is determined as the startingpoint. Thereby, an accuracy of the unwrap processing can be increased.

[0085] In the fitting module 606 of the non unwrap region, a processing,in which a phase value with regard to regions not effected unwrapprocessing is determined through function fitting, is performed. Thefunction fitting is performed in two dimension.

[0086]FIG. 8 shows in image forms a phase map which is the object forthe unwrap processing and a mask prepared prior to the unwrapprocessing. FIG. 8(a) shows a phase map before unwrap processing, andFIG. 8(b) shows a composition of the first echo threshold value mask andthe loop mask. Black rectangular regions within the inspection subjectregion indicated in white represent regions masked by the loop masks.FIG. 8(c) shows a result of unwrap processing by making use of thesemasks. In the example as illustrated, on regions 801 and 802 surroundedby white lines discontinuous portions with regard to phase variation arecaused because of improper unwrap processing. As in the above example,when the result of the unwrap processing under a predetermined conditionis improper, the processing according to the fitting module is preventedand a further unwrap processing is performed after changing the maskcondition. The changing of the mask condition includes alternation ofthe aforesaid loop mask and addition of the second echo threshold valuemask, in that (a) ON/OFF of the second echo threshold value maskprocessing and (b) changing of “maximum value of one side” used in theloop mask 604 are included. According to the study of the presentinventors, the above (a) and (b) affect significantly on the unwrapprocessing result, and the necessity of automatic unwrap processingincluding mask changing and unwrap processing properness judgement isconfirmed.

[0087] The second echo threshold value mask 607 was introduced accordingto the following knowledge. Namely, since the second echo signal isexpressed according to equation (2), in a region (W(x, y)˜F(x, y)) inwhich the intensities of water signal W(x, y) and the fat signal F(x, y)are substantially the same which exist between a region (W>F) where thewater signal intensity W(x, y) is larger than the fat signal intensityF(x, y) and a region (W<F) where the fat signal intensity is larger thanthe water signal intensity, the signal intensity S2(x, y) comes close to0 and the signal is buried under noises. Thereby, the phase of thesecond echo signal is disturbed by the noises which causes unwrap errorof the 2φ map. Therefore, a mask image is prepared with regard to thesecond echo absolute value image in which a portion exceeding a constantthreshold value is determined as 1 and a portion below the constantthreshold value is determined 0. With this mask the portion W(x, y)˜F(x,y) can be removed.

[0088] Now, the unwrap processing properness judgement step (step 505 inFIG. 5) which judges whether or not the unwrap processing 605 with theregion growing method which makes use of the above mask will beexplained. In this step in parallel with the unwrap processing theunwrap processing state map 804 as shown in FIG. 8(d) is prepared andthen based on the unwrap processing state map 804 it is judged whetherthe unwrapping is performed properly and if it is judged that theunwrapping has been performed improperly, the masking condition isaltered.

[0089] A preparation method of the unwrap processing state map 804 willbe explained with reference to FIG. 9.

[0090] At first, when performing the unwrap, a map (processing statemap) (b) having the same number of pixels as the objective phase 2φ map(a) is prepared, and the processing information performed is writtentherein. In this map the following processing state values are writtenas the initial values;

[0091] unwrap processing object pixel (not masked pixel): 0

[0092] unwrap non-processing object pixel (masked pixel): 1

[0093] All of the illustrated pixels in the drawing are not masked andare unwrap processing object pixels. Herein, as shown in (a) in FIG. 9,selecting (1) as the unwrap starting point, the unwrap processing isperformed with respect to adjacent four points in up and down and rightand left directions ((2), x, (3) and (4)). When starting the unwrapping,it is assumed that the unwrap processing has been completed only at thestarting point (1) and only the corresponding pixel is given theprocessing state value of 1. At this moment since the adjacent fourpoints representing comparison points are not yet subjected to theunwrap processing, their processing state value is 0 (a processing statemap representing the instant state is not illustrated). At the timingwhen the unwrap processing with respect to the adjacent points has beencompleted as shown in (a) of FIG. 9, the values indicating theprocessing state as shown in (b) of FIG. 9 is given. The processingstate value is determined in the following manner depending on theunwrap processing of the points to be compared.

[0094] (i) when the processing state value of a comparison point is 0;

[0095] Phase difference from the reference point<0.5π, . . . performunwrapping: processing state value=1 (condition 1)

[0096] Phase difference from the reference point>0.5π, . . . preventunwrapping: processing state value=−2 (condition 2)

[0097] The condition 2 implies to skip the unwrap processing, becausewhen the phase difference from the reference point is large, possibilityof causing unwrap error is high. In this instance, the numbers of (2),(3) and (4) are assigned according to the order of unwrapping and mark Xindicates that the unwrap processing was not performed. The pointindicated by mark X is not used as a reference point in the successiveregion growing operation.

[0098] Subsequently, the same processing is performed while shifting areference point to (2) as shown in (c) of FIG. 9. Namely, processingstate values are given to the adjacent points (5), (6) and (7) withrespect to the position of (2) according to the above conditions 1 and2. Although the position (1) is one of the adjacent points of (2), theunwrap processing for the point is already performed and the processingstate value 1 is given. However, in this instance the comparison withthe reference point (2) is again performed and the following processingstate value is given according to the comparison result.

[0099] (ii) when the processing state value of a comparison point is 1or more than 1;

[0100] Already given value and the value determined by the presentprocessing differ more than τ and, phase difference from the referencepoint<0.5π, . . . perform unwrapping: add+1 to the previous processingstate value (condition 3)

[0101] The previous phase value and the phase value obtained by thepresent processing are the same or, phase difference from the referencepoint≧0.5π, . . . prevent unwrapping: unchange the processing statevalue (condition 4)

[0102] In the present embodiment as illustrated, the results when point(2) is processed with reference to point (1) and when the point (1) isprocessed with reference to point (2) are the same, therefore, point (1)maintains the processing state value 1 as it is according to condition4. As a result, the processing state map is given as shown in (d) ofFIG. 9.

[0103] Now, it is assumed that when performing a comparison with theadjacent points using point (3) as a reference point, the processingstate value of the right side adjacent point (6) performed withreference to the reference point (2) and that performed with referenceto the reference point (3) differ more than π. In this instance, thecondition 3 stands and the processing state value 2 is given, whichimplies that since the unwrap processing results in two directionsdiffer, an indefiniteness with regard to the unwrapping is caused.Namely, when the unwrap processing state value takes more than 1, it isimplied that an indefiniteness is caused in the unwrapping.

[0104] When the unwrap processing is further advanced while successivelyshifting the reference point and the processing is performed using point(8) as the reference point as shown in (e) of FIG. 9, the down sidepoint marked by X assumes as a comparison point. The unwrap processingstate value of the point marked by X is −2. In this instance, theprocessing is performed according to the following standard.

[0105] (iii) when the processing state value of the comparison point is−2;

[0106] Phase difference from the reference point<0.5π, . . . performunwrapping: processing state value (condition 5)

[0107] Phase difference from the reference point≧0.5π, . . . performunwrapping: unchange the processing state value (condition 6)

[0108] In this instance, the point marked by X is compared with thereference point (8), and if the condition 5 is satisfied, the pointmarked by X is assigned number 19 encircled, and the unwrap processingvalue 1 is given. On the other hand, if the condition 6 is satisfied, noprocessing is performed.

[0109] As has been explained hitherto, through continuing the sameunwrap processing while shifting the reference point from smallernumbers successively the unwrap processing state map is obtained whichgives one of the processing state values to all of the unwrap processingobject pixels.

[0110]FIG. 8(d) shows in an image form thus prepared unwrap processingstate map 804. In the drawing, circumferential black region and centerblack regions 8041 are non processing object regions, therefore, theunwrap processing state thereof is 1. A center gray region 8042 is aportion where the unwrap processing has already been completed and theunwrap processing state value thereof is 1. In this unwrap processingstate map, regions indicated by white are regions having an unwrapprocessing state value more than 1. Namely, in FIG. 8(a) an uppervertical white line 8043 and three horizontal white lines 8044, 8045 and8046 at right and left sides are the regions having a unwrap processingstate value more than 1.

[0111] When observing the phase 2φ map (FIG. 8(c)) after unwrap of theabove processing state, in the region 802 surrounded by the while line,the phase discontinues at the border of vertical white line 8043 in theunwrap processing state map 804. This is because, for example, the valueunwrapped from an arrow (1) direction at the border 8043 is differentfrom that unwrapped from an arrow (2) direction thereat.

[0112] When there are points having value more than 1 in the unwrapprocessing state map as has been referred to above, there exist protonswhere the phase therein is discontinuous even after the unwrapprocessing. Therefore, in the unwrap processing properness judgementstep, when there are points having value more than 1 in the unwrapprocessing state map, it is understood that there are some errors duringunwrapping and is judged that the unwrap processing was performedimproperly. On the other hand, if unwrap processing state values for allof the pixels in the unwrap processing state map is less than 1, it isunderstood that the unwrapping has been performed properly and is judgedthat the unwrap processing is proper.

[0113] According to the judgement result, when it is judged that theunwrapping was performed improperly, reprocessing is performed afteraltering the mask condition. As has been already explained, the maskcondition alternation includes such as the addition of a new mask andalternation of the maximum value of one side in the loop mask. Anexample of the unwrap automation algorisms is shown in FIG. 10.

[0114] The automatic unwrap algorism includes processing 901 which usesthe first echo threshold value mask, processing 902 which uses thesecond echo threshold value mask and processing 903 which varies themaximum value of the loop mask.

[0115] At first, a usual unwrap processing is performed in processing901. Namely, through masking the phase 2φ map before unwrapping with thefirst echo threshold value mask noises on the phase 2φ map are removed,and further while applying a low pass filter (LPF), a loop mask isprepared. The maximum value of one side in the loop mask in thisinstance is set at a small value, for example, of about 2˜3 pixels.Subsequently, while advancing the unwrap processing with region growingmethod, the unwrap processing state map is prepared.

[0116] After the unwrap processing, it is judge with the above judgementmethod whether the unwrapping has been performed properly with referenceto the prepared unwrap processing state map (9011). If the judgement isOK, the process moves to the fitting, and if the judgement is NG, theprocess moves to a subsequent processing 902.

[0117] In the processing 902, the second echo threshold value mask 9021is applied in addition to the previously applied first echo thresholdvalue mask 9012 and the same processing as in the processing 901 isperformed. Through the application of the second echo threshold valuemask 9021 in this processing, noise contamination can be prevented in aregion (W(x, y)˜F(x, y)) in which the intensities of the water signalW(x, y) and the fat signal F(x, y) are substantially the same of whichregion exist between a region (W>F) where the water signal intensityW(x, y) is larger than the fat signal intensity F(x, Y) and a region(W<F) where the fat signal intensity is larger than the water signalintensity.

[0118] In step 9022 in this processing, it is also judged whether theunwrapping has been performed properly with reference to the unwrapprocessing state map, if the judgement is OK, the process moves to thefitting, and if the judgement is NG, the process moves to a subsequentprocessing 903.

[0119] In the processing 903, a loop mask is prepared by increasing themaximum value of one side in the loop mask (step 9031). Through theincreasing of the maximum value of one side the mask is strengthened tothereby further remove unwrap error sources. If the maximum value of oneside in the loop mask is set at a large value at the initial stage, theregion of unwrap processing is hard to grow, because unnecessarilystrong mask is applied and the accuracy of fitting of the phase 2φ mapdecreases which is performed later. Accordingly, the maximum value ofone side in the loop mask is gradually increased (in this instance byone pixel) at the timing when unwrap processing error is caused,thereby, a proper unwrap processing is performed while keeping a maximumunwrap processing region.

[0120] Subsequently, after performing unwrap processing 9032, in step9033 in this processing it is also judged whether the unwrapping hasbeen performed properly with reference to the unwrap processing statemap, if the judgement is OK, the process moves to the fitting, and ifthe judgement is NG, the process returns to the processing 903. Theprocessing 903 is repeated until the unwrap processing state map becomesOK.

[0121] In the fitting module (FIG. 6, 606), a processing of estimatingphases is performed for the regions where the masks are applied,thereby, no unwrap processing has been performed. For the phase valueestimation any known function fitting methods can be employed. Since thephase 2φ map to be determined is in two dimension, the function fittingis performed with regard to two dimension.

[0122] A map obtained by the fitting can be used as it is as the phase2φ map after fitting, however, after comparing the phase 2φ map afterfitting with the phase 2φ map before fitting for every pixel, “a phase2φ map after fitting” can be completed, by adding or subtracting onlythe most close 2nπ (n is a positive integer) with respect to thedifference before and after fitting onto the phase 2φ map beforefitting. Through effecting the above processing, a result whichcompletely reflects all of the phase information before the fitting canbe obtained. Namely, the water and fat image separation can be achievedin which even a phase offset due to local offset of the resonancefrequency f0 caused by, for example, local noises and eddy current,factors other than the static magnetic field inhomogeneity is corrected.On the other hand, a phase 2φ map after fitting without the aboveprocessing is thought to reproduce a primary static magnetic field notcontaining noise influences.

[0123] Subsequently, by making use of a phase map obtained by thefitting module, herein the static magnetic field inhomogeneity map, thephase of the second echo is corrected according to the followingequation;

S 2′(x, y)=S 2(x, y)exp(−iφ(X, y))   (10)

[0124] wherein S2′(x, y) is the second echo of which phase is corrected.

[0125] With the above equation the phase offset of the second echo whichis caused by the static magnetic field inhomogeneity during the lapsedtime τ from the first echo generation is corrected. Thereby, with thefollowing equations (11) and (12), an addition image corresponding to awater image and a subtraction image corresponding to a fat image can beobtained respectively;

S 1(x, y)+S 2′(x, y)=2W(x, y)exp(iα(x, y))   (11)

S 1(x, y)−S 2′(x, y)=2F(x, y)exp(iα(x, y))   (12)

[0126] In this instance, when assuming the phase calculation is correct,an addition image corresponding to a water image and a subtraction imagecorresponding to a fat image are in principle obtained, however, inpractice since it is possible during unwrapping of the phase 2φ map thata phase offset of 2nπ is superposed, the determination of water and fatimages can be reversed. Namely, an addition image corresponding to a fatimage and a subtraction image corresponding to a water image can beobtained.

[0127] Although these phase offsets can be prevented by adding aprocessing of varying an unwrap starting point, however, in the aboveexplained region growing method, since the unwrap processing startingpoint is automatically determined in order to permit the unwrapprocessing to be performed in a broad area, it is preferable to performa phase matching processing after the unwrap processing.

[0128] Such phase matching algorism is shown in FIG. 11. In thisprocessing, 2φ map before unwrap (a), 2φ map after unwrap (b) anddifference therebetween (c) are used. Because of the nature of theunwrap the respective values on the difference (c) take 2nπ to show adistribution of n. Then, the phase values of all pixels are shifted by±2mπ (m=0, 1, 2, . . . ) so that the phase values of 2φ maps before andafter unwrap on a region of n which appears most frequently in the abovedistribution become equal. This is based on an assumption that theregion of n which appears most frequently will greatly contribute fordeciding the resonance frequency f0 during data imaging.

[0129] Through adding such phase matching processing, a certainty ofobtaining a water image in a form of an addition image and a fat imagein a form of a subtraction image can be enhanced. However, even with thephase matching method it is possible that the water and fat images cannot be obtained correctly, in such instance, it is preferable to employanother automatic discrimination method between water and fat images aswill be explained later.

[0130] According to FIG. 10 embodiment as the mask for the unwrapprocessing a stepwise combination of the first echo threshold valuemask, the second echo threshold value mask and the loop mask whilevarying the conditions thereof is used as well as in parallel with theadvancement of the unwrap processing the unwrap processing state map isprepared to judge whether or not the unwrap processing is performedproperly, thereby, a proper unwrap processing can be performed withoutunnecessarily strengthening the mask.

[0131] Now, another embodiment of the phase 2φ map preparation moduleaccording to the present invention will be explained. In the presentembodiment, in place of the second echo threshold value mask in FIG. 10embodiment a mask making use of (second echo signal)/(first echo signal)(hereinbelow will be referred to as ec2/ec1 mask) is used.

[0132]FIG. 12 shows the unwrap automation algorism according to thepresent embodiment and the present unwrap automation algorism includes aprocessing 1001 which makes use of the first echo threshold value mask,a processing 1002 which makes use of a ec2/ec1 mask and a processing1003 which varies the maximum value of the loop mask.

[0133] The ec2/ec1 mask is a mask which determines the value (secondecho signal)/(first echo signal) and gives 1 when the determined valueis more than a predetermined threshold value and gives 0 when thedetermined value is less than the predetermined threshold value, and isintroduced to remove a phase disturbance at the border between theregion (W>F) where the water signal intensity W(x, y) is larger than thefat signal intensity F(x, y) and the region (W<F) where the fat signalintensity is larger than the water signal intensity.

[0134] According to the study of the present inventors, it was confirmedthat these special phase disturbances are caused by the computationwhich doubles the phase determined from the first echo and the secondecho and are induced by (i) existence of static magnetic fieldinhomogeneity and (ii) gradual variation from W>F to W<F. Therefore,when the value of (second echo signal)/(first echo signal) is less thanthe threshold value, through masking the concerned pixel such phasedisturbance is removed.

[0135] More specifically, a ratio of the absolute values of the firstecho image and the second echo image is determined and a mask is appliedto a region where the determined ratio is less than a threshold value mtaccording to the following in-equation (13).

|We−TE2/T2*W−Fe−TE2/T2*F|/|We−TE1/T2*W+Fe−TE1/T2*F|<mt   (13)

[0136] In the above in-equation, TE1 and TE2 are respectively TE of thefirst echo and the second echo, and T2*W and T2*F are respectively T2*of water and fat. From in-equation (13), it will be understood that thepresent ec2/ec1 mask is sensitive at the border between the region ofW>F and the region of W<F in comparison with the second echo thresholdvalue mask.

[0137] Now, the processing by the unwrap automation algorism as shown inFIG. 12 will be explained. At first in the processing 1001 the unwrapprocessing is performed by making use of the first echo threshold valuemask. Although the processing 1001 is substantially the same as theprocessing 901 in FIG. 10, in the present embodiment a processing 1011which checks before unwrapping how the region grows is added. The regiongrowing measured by the present processing is compared with a regiongrowing measured by a similar processing 1021 in the processing 1002which will be explained later, and which is used for adjusting theintensity of the ec2/ec1 mask.

[0138] In this first processing 1001 like the previous embodiment theunwrap processing state map is prepared in parallel with the unwrapprocessing, and it is judged whether each processing state value of allpixels on the map is less or more than 1 and the properness of theunwrap processing is judged. When it is judged that the unwrapprocessing has been performed properly, the process moves to the fittingmodule.

[0139] When it is judged that the unwrap processing is NG, the processmoves to the processing 1002 wherein the ec2/ec1 mask is applied to thephase 2φ map after the processing 1001. More specifically, a mask whichremoves pixels satisfying the following in-equation (14) using thethreshold value mt is applied.

Absolute value of second echo signal/Absolute value of first echosignal<mt   (14)

[0140] With this measure, as has been already explained, the portionwhere the phase disturbance was caused at the border between the region(W>F) and the region (W<F) can be removed from the unwrap processing.Subsequently, after passing the low pass filter and preparing the loopmask, the growing of the unwrap processing is measured (step 1021), andit is judged whether the growing of the unwrap processing is sufficient(step 1022). The judgement is performed through comparison of the resultat step 1011 in the processing 1001 with the result at step 1021 in theprocessing 1002.

[0141]FIG. 13 shows in image forms the result of measurement of theunwrap processing growing, and (a) in FIG. 13 is the result at thegrowing measurement step 1011 in the processing 1001 which makes use ofthe first echo threshold value mask and (b) in FIG. 13 is the result ofthe growing measurement step 1021 in the processing 1002 which makes useof the ec2/ec1 mask. Herein, regions 1111 and 1121 indicated in whiteare the growing regions of the unwrap processing and at the respectivegrowing measurement steps 1011 and 1021 in the processings 1001 and 1002areas (number of pixels) of the respective regions 1111 and 1121 asindicated in white are determined.

[0142] At step 1022, a ratio R of the areas of the regions respectivelydetermined in these steps 1011 and 1021 is determined. When the ratio Rsatisfies R≧a predetermined value (for example, 0.8), it is judged thatthe unwrap region will sufficiently grow and the process moves to theunwrap processing. On the other hand, when R<0.8, it is judged that thegrowing of unwrap region is insufficient, the process moves to step 1023where the threshold value mt of the ec2/ec1 mask is reduced and theprocessing is again respected. Such processing is repeated until R≧0.8is satisfied.

[0143] After performing the unwrapping while adjusting the thresholdvalue mt of the ec2/ec1 mask in the above manner, the unwrap processingstate map which was prepared in the step 1024 is referred to. In thepresent embodiment like the processing 1001, it may be judged whethereach processing state value of all pixels is less or more than 1, oralternatively the judgement can be modified to permit pixels having theunwrap processing state value more than 1 if the same locate in a FOVperipheral region.

[0144] More specifically, when the threshold value mt of the ec2/ec1mask which was adjusted previously reduces below mt2, the followingprocessing which permits uncertainty of unwrapping is added.

[0145] Threshold value of ec2/ec1 mask≧mt2: not permit erroneousunwrapping,

[0146] Threshold value of ec2/ec1 mask<mt2: permit even if erroneousunwrapping remains at boundary of image.

[0147] The image of the threshold value of ec2/ec1 mask<mt2 implies oneof which unwrap processing growing is weak from the outset, therefore,if the maximum value of one side of the loop mask is increased for suchimages, the growing of the unwrap processing suddenly reduces and theresult of fitting which is performed successively may become improper.Accordingly, in such instance, through allowing such pixels even iferroneous unwrapping remains at the image periphery, an excessivestrengthening of the loop mask is prevented.

[0148]FIG. 14 shows a range where such erroneous unwrapping ispermitted. Namely, a FOV peripheral region (⅙ area from the outer edgeof FOV) 1402 outside a white rectangular 1401 in FIG. 14 is permittedeven if an unwrap uncertainty exists.

[0149] Even after performing such comparatively loose unwrap processingstate judgement, when the unwrapping is NG, the process advances to thesubsequent processing 1003. The processing 1003 is the same as theprocessing 903, in that the unwrap processing is performed while varyingthe maximum value of one side of the loop mask. Herein, in step 1031 inwhich properness of the unwrap processing is judged, like the processing1002 which makes use of the ec2/ec1 mask the processing which permitsunwrapping for the region of FOV periphery can be added, even if thereexists uncertainty therein. Thereby, a growing limitation of unwrapregion due to excessive strengthening of the loop mask can be prevented.Likely, in this instance it is understood that such a loose judgementdoes not lead to deterioration of diagnosis information represented by afinal image.

[0150] As has been explained above, through advancing the processings1001, 1002 and 1003, the phase map after unwrap processing is obtained.The phase of the second echo is corrected by making use of the obtainedstatic magnetic field inhomogeneity map obtained after fitting the phasemap, and through addition and subtraction of the phase corrected secondecho and the first echo a water image and a fat image are obtained,which is the same as the data processing flow as shown in FIG. 5.

[0151] Likely in the present embodiment, the phase matching processingcan be added which removes the phase offset by comparing of the phasebefore processing with that after unwrap processing. In addition to thestatic magnetic field correction, a processing of adding or subtractingonly the most close 2nπ (n is a positive integer) with respect to thedifference before and after fitting onto the phase 2φ map before fittingcan be added after the fitting, thereby, the water and fat separationcan be achieved in which even a phase offset due to local offset of theresonance frequency f0 caused by, for example, local noises and eddycurrent is corrected.

[0152] According to FIG. 12 embodiment, since the ec2/ec1 mask which issensitive at the boundary between the region W>F and the region W<F isemployed as the mask for the unwrap processing, influences affecting theunwrap processing of the phase disturbance caused at the boundary areeliminated. Further, according to the present embodiment since thefunction of checking growing of the unwrap processing is added betweenthe processing by means of the first echo threshold value mask and theprocessing by means of the ec2/ec1 mask, the intensity of the mask canbe adjusted. Still further, with regard to the properness judgement ofthe unwrap processing state, since the judgement standard at theperipheral region is loosened, an excessive strengthening of the loopmap as well as an excessive elongation of the processing time can beprevented.

[0153] Now, still another embodiment of the phase map preparation moduleaccording to the present invention will be explained. The presentembodiment simplifies the module itself and shortens the unwrapprocessing time by locating a part of the processing outside theprocessing loop. The processing flow of the present embodiment is shownin FIG. 15.

[0154] Among the present processing flow, a processing 1501 which makesuse of the first echo threshold value mask and a processing 1503 whichalters the maximum value of one side of the loop mask are the same asthe processings 1001 and 1003 in FIG. 12, however, in a processing 1502which makes use of the ec2/ec1 mask the low pass filter processing andthe loop mask preparation processing are omitted from the processingloop which alters the threshold value of the ec2/ec1 mask until theratio of unwrap processing growing becomes more than the threshold valueto shorten the loop processing time. The simplification of theprocessing is not limited to the present embodiment, but can be appliedto other embodiments.

[0155] Further, as a further embodiment which shortens the processingtime, it is possible to reduce the matrix size when preparing phase 2φmap.

[0156] In this instance, at the first stage of the phase 2φ mappreparation a module is added which reduces the respective matrix sizesof the first echo image and the second echo image, thereafter, the 2φmap preparation is performed with respect to the reduced size images.The prepared 2φ map after fitting is restored to the original matrixsize (step 1602), thereafter, the separation processing between waterand fat is performed.

[0157]FIG. 17 shows a method of reducing matrix size. In the drawing,with the method shown by 1701 at first image data in actual space areconverted through Inverted Fourier Transformation (2D-IFT) to data inKx-Ky space, after cutting out a portion of the data, the data areconverted through Fourier Transformation to an image in actual space.Further, with the method shown by 1702 the data are simply thinned-out,for example, for every one point. With this method, some image qualitydeterioration can be caused, however, the time consumed for the FourierTransformation can be reduced by the time corresponding to thetransformation time of four times in maximum.

[0158] Hereinabove, the methods have been explained in which from twotypes of signals having different echo times TE obtained by the pulsesequence based on the 2-point Dixon method the static magnetic fieldinhomogeneity map is prepared, in this instance the automatic algorismprocessing for the unwrap processing is performed and separated waterand fat images are obtained after correcting the phase of the signals,however, the automation algorism for the unwrap processing according tothe present invention is not limited to the 2-point Dixon method, butcan be applied to an instance in which three types of signals havingdifferent echo times are successively measured as shown in FIG. 2 and astatic magnetic field inhomogeneity distribution is determined throughcomputation between the three types of signals.

[0159] Hereinbelow, a method of determining a static magnetic fieldinhomogeneity distribution according to a 3-point Dixon method will beexplained briefly. At first as shown in FIG. 2, image taking of threetimes while varying TE is performed to obtain three signals S1, S2 andS3. TE of the first echo S1 is set at an integer multiple of 2π, and TEof the second echo S2 is set longer by τ from TE of the first echo S1and TE of the third echo S3 is set further longer by τ from TE of thesecond echo.

[0160] At the time when the first echo is measured, the water signal 206and the fat signal 205 are in in-phase and have a phase 207 of whichvalue is assumed as α. At the time when the second echo is measured, thewater signal 209 and the fat signal 208 are in anti-phase, and the phaseof the water signal at this moment assumes α+φ. φ represents a phaserotation amount due to static magnetic field inhomogeneity. At the timewhen the third echo is measured, the water signal 211 are again inin-phase and of which phase value is α+2φ. Since the water signals andthe fat signals in the first and second echoes are in in-phase, throughdetermination of the phase S3(x, y)/S1(x, y) a phase rotation amount dueto the static magnetic field inhomogeneity can be determined. Namely,

S 1(x, y)=(W(x, y)+F(x, y))exp(i(α(X, y)))

S 3(x, y)=(W(x, y)+F(x, y))exp(i(α(X, y)+2φ(X, y)))

arg(S 3(x, y)/S 1(x, y))=2φ(x, y)

[0161] wherein arg ( ) implies to determine phase.

[0162] A phase map in which 2φ(x, y) is determined for all of (x, y) issubjected to an unwrap processing according to the data processing flowin FIG. 5 or FIG. 16 and FIG. 6, then the result is divided by 2 toobtain phase rotation amount φ(x, y) due to static magnetic fieldinhomogeneity. By making use of the obtained φ(x, y), the phasecorrection of the signal S2 is performed, the addition image and thesubtraction image are obtained in the same manner as in the 2-pointDixon method.

[0163] Further, in FIG. 2, an example in which signals having differentecho times are obtained by three time measurements was illustrated,however, it is possible to obtain three signals having different echotimes within a single repetition time. Further, in the presentembodiment a sequence of gradient echo method was exemplified, however,a sequence of spin echo method as shown in FIGS. 18(a) and 18(b) canalso be employed.

[0164] Further, in the above embodiment, the application of 0° and −180°two echo sequence is exemplified, however, an application of 0° and −90°two echo sequence is possible after adding necessary modification to theformer, in this instance, 2φ map is modified to 4φ map.

[0165] Further, other than for obtaining the separated water and fatimages, the present automation algorism for the unwrap processing can beapplied generally to an MRI device having a function of determining aphase map such as static magnetic field inhomogeneity map. The aboveautomation algorism for the unwrap processing, for example, can also beused for an MRI device provided with an auto slimming function which,after obtaining a static magnetic field inhomogeneity map, drives simcoils so as to generates magnetic field having the same magnitude but ofopposite polarity thereto, and an MRI device which permits phasecorrection with regard to such as distortion and position offset inimages obtained by sequences susceptible to static magnetic fieldinhomogeneity such as EPI (Echo Planar Imaging) method.

[0166] Now, as a second aspect of the present invention, a method ofautomatically discriminating a water image and a fat image from anaddition image and a subtraction image in the water and fat separatedimage taking will be explained.

[0167] As has been explained previously, with the Dixon method, if thephase computation is correct, a water image in a form of addition imageand a fat image in a form of subtraction image are in principleobtained, however, in practice such is sometimes reversed and furthersuch can be caused even when a phase matching is performed after unwrapprocessing. Namely, in connection with the unwrap processing of thephase 2φ map uncertainty of 2nπ always exists.

[0168] In the automatic discrimination method according to the presentinvention, under a precondition of the above referred to uncertainty inassociation with the unwrap processing, a method of automaticallydiscriminating two types of images obtained through computation isprovided. For this purpose, two discrimination methods are employed. (1)A method of comparing ratios of pixel values of the first echo image andthe second echo image, in that the signal ratios, and (2) a method ofdirectly comparing pixel values of the addition and subtraction images.These methods will be explained in detail hereinbelow.

[0169] (1) The method of comparing ratios of pixel values of the firstecho image and the second echo image is based on an assumption that withregard to the ratio of [pixel value of the second echo image]/[pixelvalue of the first echo image] (hereinafter will be referred to assignal ratio), the water signal shows a larger value. Namely, since T2value of water signal is longer in comparison with that of the fatsignal, the signal attenuation thereof between the first echo image andthe second echo image is weak, therefore, the signal ratio thereof givesa larger value. Strictly speaking, the signal attenuation between thefirst echo image and the second echo image is T2* attenuation, becausethe influence such as due to the static magnetic field inhomogeneity isincluded, however, difference of the signal ratios of the water signaland the fat signal is held unchanged. Therefore, in the presentdiscrimination method, the above fact is made use of.

[0170]FIG. 19 shows an algorism for deciding between a water image and afat image according to the signal ratios. At first with regard to theaddition image (a) and the subtraction image (b) high intensity signalregions are respectively extracted as high pixel value regions (c) and(d). In this instance, it is preferable that number of pixels in theregion extracted is about 1% in the region having signals (namely, pixelnumber on the inspection subject region).

[0171] On the other hand, a signal ratio of the first and second echoimages for every pixel on the inspection subject region is determined.On the thus determined signal ratio image the high pixel value regions(c) and (d) which are formed by extracting a high intensity signalregion are superposed to form an image (e), and an average value of thesignal ratios on the portion where the high pixel value region (c) ofthe addition image is superposed is compared with an average value ofthe signal ratios on the portion where the high pixel value region (d)of the subtraction image is superposed.

[0172] Since the signal ratio of the water signal is presumed larger ashas been explained above, as the result of the above comparison, theimage having a larger value of signal ratio is judged as the waterimage. Namely, among the signal ratios of the addition image extractionregion and of the subtraction image extraction region, one having alarger value is judged as the water image and one having a smaller valueis judged as the fat image.

[0173] In case of the 3-point Dixon method, by plotting the pixel valuesof the first, second and third echo images in an exponential function,attenuation coefficients can be obtained, and one having a largerattenuation coefficient is judged as the fat image.

[0174] The accuracy of the above method can be further enhanced, whenthe following condition is added in which when a difference (or ratio)between the signal ratio of the addition image extraction region and theratio of the subtraction image extraction region is more than apredetermined value, one having a larger value of signal ratio is judgedas the water image.

[0175] In actual measurement, with regard to some tissue in which waterprotons exist, T2 thereof is shorter than that of bulk phase water andcomes close to that of the fat signal, as a result, a measurement errorcan be caused. For example, at the portions such as ankle and knee, amuscle as a region showing a high water signal and subcutaneous fat as aregion showing a high fat signal are extracted, however, since themolecules existing in the muscle couple with proteins, T2 thereof isshorter than of bulk phase water. Therefore, it is understood that thesignal ratio of the water signal comes close to the signal ratio of thesubcutaneous fat signal which makes their discrimination difficult.

[0176] Therefore, among the signal ratio of the addition imageextraction region and the signal ratio of the subtraction imageextraction region as has been explained above, only when a ratio of the“larger signal ratio” to the “smaller signal ratio” is more than athreshold value m (>1), a processing is performed to determine the“larger signal ratio” of the extraction region as the water image andthe “smaller signal ratio” thereof as the fat image. Thereby, portionsincluding errors are removed and the accuracy of judgement can beenhanced. The value of the above threshold m is not limited, however,according to the study of the inventors it is understood that m=1.2 ortherearound is preferable.

[0177] However, when adding the above condition, if the ratio of the“larger signal ratio” to the “smaller signal ratio” satisfies thefollowing inequation, the water and fat images can not be determinedwith the addition and subtraction images;

1<[larger signal ratio]/[smaller signal ratio]≦m

[0178] Accordingly, the automatic discrimination method of the presentinvention uses in parallel the method (2) in which the pixel values ofthe addition and subtraction images are directly compared as a secondmethod.

[0179] The method of directly comparing the pixel values of the additionand subtraction images makes use of the fact that the maximum pixelvalue of the fat image is larger than the maximum pixel value of thewater image under a predetermined contrast determined by an image takingmethod employed or the opposite relation thereof. For example, in thespin echo (SE) sequence a T1 emphasized image is generally taken,therefore, under the contrast in such instance the maximum pixel valueof the fat image is larger than the maximum pixel value of the waterimage. Therefore, in the present embodiment the water and fat images arediscriminated by making use of the above feature.

[0180]FIG. 20 shows an algorism for realizing the above method (2).Likely, in this method at first from an addition image (a) and asubtraction image (b) high pixel value regions (c) and (d) areextracted. Subsequently, averages of pixel values of the images (a) and(b) with respect to the respective extracted regions are determined. (e)and (f) in FIG. 20 show images in which the images (a) and (b) arerespectively superposed over the extracted images (c) and (d) in orderto determine the pixel values with respect to the extracted regions.Thereafter, the average values of the determined pixel values arecompared.

[0181] As has been explained above, under the contrast of T1 emphasizedimage, the average value of the fat pixel values is larger than theaverage value of the water pixel values, namely, it is expected tosatisfies the following inequation;

(average of fat pixel values)/(average of water pixel values)>1

[0182] Accordingly, among the addition image and the subtraction image,the image having the larger average pixel value is judged as the fatimage and the image having the smaller average pixel value is judged asthe water image.

[0183] With this method, likely the judgement accuracy can be enhancedby eliminating a measurement error possibly caused during actualmeasurement. For this purpose, among the addition image and thesubtraction image, a ratio between the “image having a larger averagepixel value” and the “image having a smaller average pixel value” istaken and when the ratio shows to be larger than a predeterminedthreshold value p(>1), the image having a larger average pixel value isjudged as the fat image and the image having a smaller average pixelvalue is judged as the water image.

[0184] Likely, in this embodiment, when the ratio [image having largeraverage pixel value]/[image having smaller average pixel value]satisfies the following inequation;

1≦[image having larger average pixel value]/[image having smalleraverage pixel value]≦p

[0185] the water and fat images can not be judged from the addition andsubtraction images in the above manner, however, if the present methodis used in parallel with the above method (1), the water and fat imagescan be discriminated.

[0186] Further, in the method (2) when the first echo image and thesecond echo image have other contrast than that of T1, the method can beapplied in the same manner by varying the threshold values m and p.

[0187] When applying both methods, both methods can be applied in such amanner that one of the methods is used first and if the judgement cannot be made with the method, then the other method is used.

[0188] After performing the discrimination as above, an indication as“water image” or “fat image” is applied on the image displayed. With theabove method, since an automatic image discrimination can be performedeven for tissues in which a tissue containing water and a tissuecontaining fat are interlaced in complex, a diagnosis of an inspectionsubject can be performed efficiently.

[0189] Automatic discrimination methods between water and fat imageshave been explained hitherto. The application of the present automaticdiscrimination method is not limited to the Dixon method, but thepresent method can be applied to a general method in which water and fatimages are determined through computation of MR signals obtained atdifferent echo times. In such instance, applicable image taking sequenceis not only the sequence in which two echoes are obtained by a singleexcitation, but also a single scan sequence such as echo planar imaging(EPI) method and fast spin echo (FSE) method in which echoes necessaryfor one sheet image are obtained by a single excitation. In suchinstance, image taking time is further shortened.

[0190] In the above embodiments, the separation of water and fat isexemplified, however, if the image taking method relates to obtain twotypes of spin signals by making use of the chemical shift, the presentinvention is applicable to other combinations of materials, for example,with regard to separation of water and silicon, and water and NAA.

[0191] According to the present invention, when preparing a phase offsetmap due to such as a static magnetic field inhomogeneity by making useof plural signals having different echo times, an algorism whichoptimizes an unwrap processing is provided. Through applying suchalgorism to a water and fat separated image acquiring method such asDixon method with static magnetic field correction, the water and fatseparated images can be acquired in fully automatic.

[0192] Further, according to the present invention, in the method inwhich water and fat separated images are acquired through computationbetween plural signals having different echo times, a method whichautomatically discriminate either an addition image or a subtractionimages as a water image or a fat image is provided. Through applyingsuch method to a water and fat separated image acquiring method such asDixon method with static magnetic field correction, the water and fatimages can be drawn in fully automatic.

1. A magnetic resonance imaging device which is provided with a magnetic field generation means which respectively generates a high frequency magnetic field and a gradient magnetic field in a space where a static magnetic field is formed, a signal processing means which detects a nuclear magnetic resonance signal generated from an inspection subject placed in the space and reconstructs an image therefrom and a display means which displays the reconstructed image, wherein the signal processing means performs, by making use of at least more than one nuclear magnetic resonance signals having different times (TM) from irradiation of the high frequency magnetic field signal and generation of the nuclear magnetic resonance signals, a computation for determining phase offset distribution between the signals, an unwrap processing for correcting a principal value rotation caused in the computation and at the same time performs a judgement whether the unwrap processing is proper by making use of a parameter representing the unwrap processing state.
 2. A magnetic resonance imaging device according to claim 1, wherein the signal processing means, after correcting the nuclear magnetic resonance signals based on the phase offset distribution which is judged as the unwrap processing has been performed properly, reconstructs an image with regard to two types of nuclear spins having different chemical shifts through computation between the signals.
 3. A magnetic resonance imaging device which is provided with a magnetic field generation means which respectively generates a high frequency magnetic field and a gradient magnetic field in a space where a static magnetic field is formed, a signal processing means which detects a nuclear magnetic resonance signal generated from an inspection subject placed in the space and reconstructs an image therefrom and a display means which displays the reconstructed image, wherein the signal processing means, by making use of at least more than one nuclear magnetic resonance signals having different times (TM) from irradiation of the high frequency magnetic field signal and generation of the nuclear magnetic resonance signals, reconstructs more than one original images, further reconstructs two types of display images with regard to two types of nuclear spins having different chemical shifts through computation between these original images and performs an automatic discrimination on the correspondence between the obtained two types of the display images and the two types of the nuclear spins from a ratio of pixel values of the more than one original images and/or pixel values of the two types of the display images.
 4. A magnetic resonance imaging device which is provided with a magnetic field generation means which respectively generates a high frequency magnetic field and a gradient magnetic field in a space where a static magnetic field is formed, a signal processing means which detects a nuclear magnetic resonance signal generated from an inspection subject placed in the space and reconstructs an image therefrom and a display means which displays the reconstructed image, wherein the signal processing means, by making use of at least more than one nuclear magnetic resonance signals having different times (TM) from irradiation of the high frequency magnetic field signal and generation of the nuclear magnetic resonance signals, a computation for determining a phase offset distribution between the signals, an unwrap processing for the correcting a principal value rotation caused in the computation and at the same time performs a judgement whether the unwrap processing is proper by making use of a parameter representing the unwrap processing state, and by making use of the nuclear magnetic resonance signals corrected based on the phase offset distribution judged as properly unwrap processed, reconstructs more than one original images, further reconstructs two types of display images with regard to two types of nuclear spins having different chemical shifts through computation between these original images and performs an automatic discrimination on the correspondence between the obtained two types of the display images and the two types of the nuclear spins from a ratio of pixel values of the more than one original images and/or pixel values of the two types of the display images.
 5. A magnetic resonance imaging method in which an inspection subject is laid in a space where a static magnetic field is formed, a high frequency magnetic field is irradiated onto the inspection subject while applying a gradient field to the static magnetic field, a nuclear magnetic resonance signal generated from the inspection subject in response to the irradiation is detected, an image of a predetermined portion of the inspection subject is reconstructed based on the detected signal and the reconstructed image is displayed, comprising: a step of preparing first and second echo image data by making use of respectively plural first and second echo signals each having different echo time from the high frequency magnetic field irradiation to the nuclear magnetic resonance signal generation; a step of preparing a phase rotation amount distribution map representing a static magnetic field inhomogeneity from the first and second echo image data; a step of applying a first mask prepared based on the first echo image data to the phase rotation amount distribution map; a step of further applying a first loop mask to the phase rotation amount distribution map to which the first mask is applied; a step of performing a first unwrap processing with regard to respective pixel portions on the phase rotation amount distribution map to which the first mask and the first loop mask are applied but the portions not covered thereby; a step of preparing a first unwrap processing state map in parallel with the first unwrap processing; a step of judging properness of the first unwrap processing based on the prepared first unwrap processing state map; a step of preparing an unwrap phase rotation amount distribution map by executing a function fitting with regard to pixel portions of non unwrap processing in the phase rotation amount distribution map which is judged as the unwrap processing is proper; a step of effecting a phase correction to the second echo image data based on the unwrap phase rotation amount distribution map; a step of preparing an addition image data by adding the first echo image data and the phase corrected second echo image data; a step of preparing a subtraction image data by subtracting the phase corrected second echo image data from the first echo image data; and a step of discriminating one of the addition image data and the subtraction image data as a water image data and the other as a fat image data based on a ratio of pixel values determined for every pixel of the first and second echo image data.
 6. A magnetic resonance imaging method according to claim 5, further comprising; a step of discriminating one of the addition image data and the subtraction image data as a water image data and the other as a fat image data based on respective pixel values of predetermined portions of the addition image data and the subtraction image data.
 7. A magnetic resonance imaging method according to claim 6, wherein when the first unwrap processing is judged improper in the first unwrap processing properness judgement step, further comprising: a step of applying a second mask which is prepared based on the second echo image data to the phase rotation amount distribution map; a step of performing a second unwrap processing on respective pixel portions in the phase rotation amount distribution map to which the second mask is applied but the portions not covered thereby; a step of preparing a second unwrap processing state map in parallel with the second unwrap processing; and a step of judging properness of the second unwrap processing based on the prepared second unwrap processing state map.
 8. A magnetic resonance imaging method according to claim 6, wherein when the first unwrap processing is judged improper in the first unwrap processing properness judgement step, further comprising a step of increasing one pixel by one pixel the loop maximum value of the first loop mask until the judgement changes from improper to proper.
 9. A magnetic resonance imaging method according to claim 7, wherein the second mask is prepared based on a ratio (ec2/ec1) of the second echo image data with respect to the first echo image data, and further comprising: a step of measuring a growing of the second unwrap processing prior to the second unwrap processing step; a step of judging whether a ratio of the measured second unwrap processing growing with respect to the measured first unwrap processing growing is more than a predetermined value; and a step of reducing the mask threshold value of the second mask when the ratio is less than the predetermined value.
 10. A magnetic resonance imaging method according to claim 5, further comprising: a step of reducing a matrix size of the first and second image data prior to the phase rotation amount map preparation step; and a step of restoring the matrix size to the original one prior to effecting the phase correction to the second echo image data.
 11. A magnetic resonance imaging method in which an inspection subject is laid in a space where a static magnetic field is formed, a high frequency magnetic field is irradiated onto the inspection subject while applying a gradient field to the static magnetic field, a nuclear magnetic resonance signal generated from the inspection subject in response to the irradiation is detected, an image of a predetermined portion of the inspection subject is reconstructed based on the detected signal and the reconstructed image is displayed, comprising: a step of preparing first, second and third echo image data by making use of respectively plural first, second and third echo signals each having different echo time from the high frequency magnetic field irradiation to the nuclear magnetic resonance signal generation; a step of preparing a phase rotation amount distribution map representing a static magnetic field inhomogeneity from the first and third echo image data; a step of applying a first mask prepared based on the first echo image data to the phase rotation amount distribution map; a step of further applying a first loop mask to the phase rotation amount distribution map to which the first mask is applied; a step of performing a first unwrap processing with regard to respective pixel portions on the phase rotation amount distribution map to which the first mask and the first loop mask are applied but the portions not covered thereby; a step of preparing a first unwrap processing state map in parallel with the first unwrap processing; a step of judging properness of the first unwrap processing based on the prepared first unwrap processing state map; a step of preparing an unwrap phase rotation amount distribution map by executing a function fitting with regard to pixel portions of non unwrap processing in the phase rotation amount distribution map which is judged as the unwrap processing is proper; a step of effecting a phase correction to the second echo image data based on the unwrap phase rotation amount distribution map; a step of preparing an addition image data by adding the first echo image data and the phase corrected second echo image data; a step of preparing a subtraction image data by subtracting the phase corrected second echo image data from the first echo image data; and a step of discriminating one of the addition image data and the subtraction image data as a water image data and the other as a fat image data based on a ratio of pixel values determined for every pixel of the first and second echo image data. 